This paper presents a method for detecting speech under stress using Self-Organizing Maps. Most people who are exposed to stressful situations can not adequately respond to stimuli. Army, police, and fire department occupy the largest part of the environment that are typical of an increased number of stressful situations. The role of men in action is controlled by the control center. Control commands should be adapted to the psychological state of a man in action. It is known that the psychological changes of the human body are also reflected physiologically, which consequently means the stress effected speech. Therefore, it is clear that the speech stress recognizing system is required in the security forces. One of the possible classifiers, which are popular for its flexibility, is a self-organizing map. It is one type of the artificial neural networks. Flexibility means independence classifier on the character of the input data. This feature is suitable for speech processing. Human Stress can be seen as a kind of emotional state. Mel-frequency cepstral coefficients, LPC coefficients, and prosody features were selected for input data. These coefficients were selected for their sensitivity to emotional changes. The calculation of the parameters was performed on speech recordings, which can be divided into two classes, namely the stress state recordings and normal state recordings. The benefit of the experiment is a method using SOM classifier for stress speech detection. Results showed the advantage of this method, which is input data flexibility.

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

This article describes a system for evaluating the credibility of recordings with emotional character. Sound recordings form Czech language database for training and testing systems of speech emotion recognition. These systems are designed to detect human emotions in his voice. The emotional state of man is useful in the security forces and emergency call service. Man in action (soldier, police officer and firefighter) is often exposed to stress. Information about the emotional state (his voice) will help to dispatch to adapt control commands for procedure intervention. Call agents of emergency call service must recognize the mental state of the caller to adjust the mood of the conversation. In this case, the evaluation of the psychological state is the key factor for successful intervention. A quality database of sound recordings is essential for the creation of the mentioned systems. There are quality databases such as Berlin Database of Emotional Speech or Humaine. The actors have created these databases in an audio studio. It means that the recordings contain simulated emotions, not real. Our research aims at creating a database of the Czech emotional recordings of real human speech. Collecting sound samples to the database is only one of the tasks. Another one, no less important, is to evaluate the significance of recordings from the perspective of emotional states. The design of a methodology for evaluating emotional recordings credibility is described in this article. The results describe the advantages and applicability of the developed method.

This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

Global System for Mobile communication (GSM) is the most widespread technology for mobile communications in the world and serving over 7 billion users. Since first publication of system documentation there has been notified a potential safety problem’s occurrence. Selected types of attacks, based on the analysis of the technical feasibility and the degree of risk of these weaknesses, were implemented and demonstrated in laboratory of the VSB-Technical University of Ostrava, Czech Republic. These vulnerabilities were analyzed and afterwards possible attacks were described. These attacks were implemented using open-source tools, software programmable radio USRP (Universal Software RadioPeripheral) and DVB-T (Digital Video Broadcasting – Terrestrial) receiver. GSM security architecture is being scrutinized since first public releases of its specification mainly pointing out weaknesses in authentication and ciphering mechanisms. This contribution also summarizes practically proofed and used scenarios that are performed using opensource software tools and variety of scripts mostly written in Python. Main goal of this paper is in analyzing security issues in GSM network and practical demonstration of selected attacks.

Intermodal container monitoring is considered a major security issue in many major logistic companies and countries worldwide. Current representation of the problem, we face today, originated in 2002, right after the 9/11 attacks. Then, a new worldwide Container Security Initiative (CSI, 2002) was considered that shaped the perception of the transportation operations. Now more than 80 larger ports all over the world contribute to its further development and integration into everyday transportation operations and improve the regulations for the developing regions. Although, these new improvements allow us to feel safer and secure, constant management of transportation operations has become a very difficult problem for conventional data analysis methods and information systems. The paper deals with a proposal of a whole new concept for the improvement of the Containers Security Initiative (CSI) by virtually connecting safety, security processes and systems. A conceptual middleware approach with deployable intelligent agent modules is proposed to be used with possible scenarios and a testbed is used to test the solution. Middleware examples are visually programmed using National Instruments LabView software packages and Wireless sensor network hardware modules. An experimental software is used to evaluate he solution. This research is a contribution to the intermodal transportation and is intended to be used as a means or the development of intelligent transport systems.

The paper is focused on the building ad-hoc GSM network based on open source software and low-cost hardware. The created Base Transmission Station can be deployed and put into operation in a few minutes in a required area to ensure private communication between connected GSM mobile terminals. The convergence between BTS station and the other networks is possible through IP network. The paper tries to define connection parameters to provide sufficient quality of voice service between the GSM network and IP Multimedia Subsystem. The paper brings practical results of voice call quality measurement between users inside BTS station mobile network and users inside IP Multimedia Subsystem network. The calls are simulated by low-cost embedded solution for speech quality measurement in GSM network. This tool is under development of our laboratory and allows automatic speech quality measurement of any GSM or UMTS mobile network. The Perceptual Evaluation of Speech Quality method is used to get final comparable results. The communication between BTS station and connected networks has to be secured against the interception from the third party. The influence of the securing method for quality of service is presented in detail. Paper, apart from the quality of service measurement section, describes technical requirements for successful interconnection between BTS and IMS networks. The authentication, authorization and accounting methods in roaming between BTS and IMS system are presented too.

It is well known that Quantum Key Distribution (QKD) can be used with the highest level of security for distribution of the secret key, which is further used for symmetrical encryption. B92 is one of the oldest QKD protocols. It uses only two non-orthogonal states, each one coding for one bit-value. It is much faster and simpler when compared to its predecessors, but with the idealized maximum efficiencies of 25% over the quantum channel. B92 consists of several phases in which initial key is significantly reduced: secret key exchange, extraction of the raw key (sifting), error rate estimation, key reconciliation and privacy amplification. QKD communication is performed over two channels: the quantum channel and the classical public channel. In order to prevent a man-in-the-middle attack and modification of messages on the public channel, authentication of exchanged values must be performed. We used Wegman-Carter authentication because it describes an upper bound for needed symmetric authentication key. We explained the reduction of the initial key in each of QKD phases.

Nowadays, the interest in real-time services, like audio and video, is growing. These services are mostly transmitted over packet networks, which are based on IP protocol. It leads to analyses of these services and their behavior in such networks which are becoming more frequent. Video has become the significant part of all data traffic sent via IP networks. In general, a video service is one-way service (except e.g. video calls) and network delay is not such an important factor as in a voice service. Dominant network factors that influence the final video quality are especially packet loss, delay variation and the capacity of the transmission links. Analysis of video quality concentrates on the resistance of video codecs to packet loss in the network, which causes artefacts in the video. IPsec provides confidentiality in terms of safety, integrity and non-repudiation (using HMAC-SHA1 and 3DES encryption for confidentiality and AES in CBC mode) with an authentication header and ESP (Encapsulating Security Payload). The paper brings a detailed view of the performance of video streaming over an IP-based network. We compared quality of video with packet loss and encryption as well. The measured results demonstrated the relation between the video codec type and bitrate to the final video quality.

Impact of changes in blood pressure and pulse from human speech is disclosed in this article. The symptoms of increased physical activity are pulse, systolic and diastolic pressure. There are many methods of measuring and indicating these parameters. The measurements must be carried out using devices which are not used in everyday life. In most cases, the measurement of blood pressure and pulse following health problems or other adverse feelings. Nowadays, research teams are trying to design and implement modern methods in ordinary human activities. The main objective of the proposal is to reduce the delay between detecting the adverse pressure and to the mentioned warning signs and feelings. Common and frequent activity of man is speaking, while it is known that the function of the vocal tract can be affected by the change in heart activity. Therefore, it can be a useful parameter for detecting physiological changes. A method for detecting human physiological changes by speech processing and artificial neural network classification is described in this article. The pulse and blood pressure changes was induced by physical exercises in this experiment. The set of measured subjects was formed by ten healthy volunteers of both sexes. None of the subjects was a professional athlete. The process of the experiment was divided into phases before, during and after physical training. Pulse, systolic, diastolic pressure was measured and voice activity was recorded after each of them. The results of this experiment describe a method for detecting increased cardiac activity from human speech using artificial neural network.

Recent years have been characterized by an increase in the air traffic. More attention over micro-economic and macroeconomic indexes would be strategic to gather and enhance the safety of a flight and customer needing, for communicating by wireless handhelds on-board aircrafts. Thus, European Telecommunications Standards Institute (ETSI) proposed a GSM On Board (GSMOBA) system as a possible solution, allowing mobile terminals to communicate through GSM system on aircraft, avoiding electromagnetic interferences with radio components aboard. The main issues are directly related with interferences that could spring-out when mobile terminals attempt to connect to ground BTS, from the airplane. This kind of system is able to resolve the problem in terms of conformance of Effective Isotropic Radiated Power (EIRP) limits, defined outside the aircraft, by using an On board BTS (OBTS) and modeling the relevant key RF parameters on the air. The main purpose of this work is to illustrate the state-of-the-art of literature and previous studies about the problem, giving also a good detail of technical and normative references.

Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis
of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically
based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as
a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on
these honeypots is collected on a centralized server and then classified. This classification is based on different
mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of
used neural network and also information about implementation of this network. The learning set for this neural network
is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real
attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network
capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate
attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a
different part of networks, which are logically or geographically divided and use the information from one network to
harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and
classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.

In this paper the predictive model for speech quality estimation is described. This model allows its user to gain the
information about the speech quality in VoIP networks without the need of performing the actual call and the
consecutive time consuming sound file evaluation. This rapidly increases usability of the speech quality measurement
especially in high load networks, where the actual processing of all calls is rendered difficult or even impossible. This
model can reach its results that are highly conformant with the PESQ algorithm only based on the network state
parameters that are easily obtainable by the commonly used software tools. Experiments were carried out to investigate
whether different languages (English, Czech) have an effect on perceived voice quality for the same network conditions
and the language factor was incorporated directly into the model.

Emotional states of humans and their impact on physiological and neurological characteristics are discussed in this
paper. This problem is the goal of many teams who have dealt with this topic. Nowadays, it is necessary to increase the
accuracy of methods for obtaining information about correlations between emotional state and physiological changes. To
be able to record these changes, we focused on two majority emotional states. Studied subjects were psychologically
stimulated to neutral - calm and then to the stress state. Electrocardiography, Electroencephalography and blood pressure
represented neurological and physiological samples that were collected during patient’s stimulated conditions. Speech
activity was recording during the patient was reading selected text. Feature extraction was calculated by speech
processing operations. Classifier based on Gaussian Mixture Model was trained and tested using Mel-Frequency Cepstral
Coefficients extracted from the patient's speech. All measurements were performed in a chamber with electromagnetic
compatibility. The article discusses a method for determining the influence of stress emotional state on the human and
his physiological and neurological changes.

This paper concerns available steganographic techniques that can be used for sending hidden data through public
network. Typically, in steganographic communication it is advised to use popular/often used method for sending hidden
data and amount of that data need to be high as much as possible. We confirmed this by choosing a Domain Name
System (DNS) as a vital protocol of each network and choosing Distributed denial of service (DDoS) attacks that are
most popular network attacks currently represented in the world. Apart from characterizing existing steganographic
methods we provide new insights by presenting two new techniques. The first one is network steganography solution
which exploits free/unused protocols fields and is known for IP, UDP or TCP protocols, but has never been applied to
DNS (Domain Name Server) which are the fundamental part of network communications. The second explains the usage
of DNS Amplification DDoS Attack to send seamlessly data through public network. The calculation that was performed
to estimate the total amount of data that can be covertly transferred by using these technique, regardless of steganalysis,
is included in this paper.

The paper deals with presentation of the IVAS system within the 7FP EU INDECT project. The INDECT project aims at
developing the tools for enhancing the security of citizens and protecting the confidentiality of recorded and stored
information. It is a part of the Seventh Framework Programme of European Union. We participate in INDECT portal and
the Interactive Video Audio System (IVAS). This IVAS system provides a communication gateway between police
officers working in dispatching centre and police officers in terrain. The officers in dispatching centre have capabilities
to obtain information about all online police officers in terrain, they can command officers in terrain via text messages,
voice or video calls and they are able to manage multimedia files from CCTV cameras or other sources, which can be
interesting for officers in terrain. The police officers in terrain are equipped by smartphones or tablets. Besides common
communication, they can reach pictures or videos sent by commander in office and they can respond to the command via
text or multimedia messages taken by their devices. Our IVAS system is unique because we are developing it according
to the special requirements from the Police of the Czech Republic. The IVAS communication system is designed to use
modern Voice over Internet Protocol (VoIP) services. The whole solution is based on open source software including
linux and android operating systems. The technical details of our solution are presented in the paper.

New applications in wireless environments are increasing and keeping even more interests from the developer companies and researchers. In particular, in these last few years the government and institutional organization for road safety spent a lot of resources and money to promote Vehicular Ad-Hoc Network (VANET) technology, also car manufactures are giving a lot of contributions on this field as well. In our paper, we propose an innovative system to increase road safety, matching the requests of the market allowing a cooperation between on-board devices. The vehicles are equipped with On Board Unit (OBU) and On Board Radar Unit (OBRU), which can spread alerting messages around the network regarding warning and dangerous situations exploiting IEEE802.llp standard. Vehicles move along roads observing the environment, traffic and road conditions, and vehicles parameters as well. These information can be elaborated and shared between neighbors, Road Side Unit (RSU)s and, of course, with Internet, allowing inter-system communications exploiting an Road Traffic Manager (RTM). Radar systems task it the detection of the environment in order to increase the knowledge of current conditions of the roads, for example it is important to identify obstacles, road accidents, dangerous situations and so on. Once detected exploiting onboard devices, such as Global Position System (GPS) receiver it is possible to know the exact location of the caught event and after a data elaboration the information is spread along the network. Once the drivers are advised, they can make some precautionary actions such as reduction of traveling speed or modification of current road path. In this work the routing algorithms, which have the main goal to rapidly disseminate information, are also been investigated.

Many recent research efforts have confirmed that, given the natural evolution of telecommunication systems, they can be
approached by a new modeling technique, not based yet on traditional approach of graphs theory. The branch of complex
networking, although young, is able to introduce a new and strong way of networks modeling, nevertheless they are
social, telecommunication or friendship networks. In this paper we propose a new modeling technique applied to
Wireless Sensor Networks (WSNs). The modeling has the purpose of ensuring an improvement of the distributed
communication, quantifying it in terms of clustering coefficient and average diameter of the entire network. The main
idea consists in the introduction of hybrid Data Mules, able to enhance the whole connectivity of the entire network. The
distribution degree of individual nodes in the network will follow a logarithmic trend, meaning that the most of the nodes
are not necessarily adjacent but, for each pair of them, there exists a relatively short path that connects them. The
effectiveness of the proposed idea has been validated thorough a deep campaign of simulations, proving also the power
of complex and small-world networks.

The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in
removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of
Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked
as telecommunication providers often focus on increasing network capacity, expansion of services offered and their
enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication
chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal
processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress
noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice
which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an
intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was
applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of
DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice
sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution
of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.

The paper deals with the increasing accuracy of voice authentication methods. The developed algorithm first extracts
segmental parameters, such as Zero Crossing Rate, the Fundamental Frequency and Mel-frequency cepstral coefficients
from voice. Based on these parameters, the neural network classifier detects the speaker's emotional state. These
parameters shape the distribution of neurons in Kohonen maps, forming clusters of neurons on the map characterizing a
particular emotional state. Using regression analysis, we can calculate the function of the parameters of individual
emotional states. This relationship increases voice authentication accuracy and prevents unjust rejection.

This article discusses a danger alert system created as a part of the research project at Department of
Telecommunications of Technical University of Ostrava. The aim of the system is to distribute pre-recorded voice
messages in order to alert the called party in danger. This article describes individual technologies, which the application
uses for its operation as well as issues relating to hardware requirements and transfer line bandwidth load. The article
also describes new algorithms, which had to be developed in order to ensure the reliability of the system. Our intent is
focused on disaster management, the message, which should be delivered within specified time span, is typed in the
application and text-to-speech module ensures its transformation to a speech format, after that a particular scenario or
warned area is selected and a target group is automatically unloaded. For this purpose, we have defined XML format for
delivery of phone numbers which are located in the target area and these numbers are obtained from mobile BTS's (Base
transmission stations). The benefit of such communication compared to others, is the fact, that it uses a phone call and,
therefore, it is possible to get feedback who accepted the message and to improve efficiency of alert system. Finally, the
list of unanswered calls is exported and these users can be informed via SMS.

This article deals about embedded SIP communication server with an easy integration into the computer network based
on open source solutions and its effective defense against the most frequent attack in the present - Denial of Service. The
article contains brief introduction into the Bright Embedded Solution for IP Telephony – BESIP and describes the most
common types of DoS attacks, which are applied on SIP elements of the VoIP infrastructure including the results of
defensive mechanism that has been designed.

There are many ways of getting real data about malicious activity in a network. One of them relies on masquerading
monitoring servers as a production one. These servers are called honeypots and data about attacks on them brings us
valuable information about actual attacks and techniques used by hackers. The article describes distributed topology of
honeypots, which was developed with a strong orientation on monitoring of IP telephony traffic. IP telephony servers
can be easily exposed to various types of attacks, and without protection, this situation can lead to loss of money and
other unpleasant consequences. Using a distributed topology with honeypots placed in different geological locations and
networks provides more valuable and independent results. With automatic system of gathering information from all
honeypots, it is possible to work with all information on one centralized point. Communication between honeypots and
centralized data store use secure SSH tunnels and server communicates only with authorized honeypots. The centralized
server also automatically analyses data from each honeypot. Results of this analysis and also other statistical data about
malicious activity are simply accessible through a built-in web server. All statistical and analysis reports serve as
information basis for an algorithm which classifies different types of used VoIP attacks. The web interface then brings a
tool for quick comparison and evaluation of actual attacks in all monitored networks. The article describes both, the
honeypots nodes in distributed architecture, which monitor suspicious activity, and also methods and algorithms used on
the server side for analysis of gathered data.

SIP proxy server is without any doubts centerpiece of any SIP IP telephony infrastructure. It also often provides other
services than those related to VoIP traffic. These softswitches are, however, very often become victims of attacks and
threats coming from public networks. The paper deals with a system that we developed as an analysis and testing tool to
verify if the target SIP server is adequately secured and protected against any real threats. The system is designed as an
open-source application, thus allowing independent access and is fully extensible to other test modules.

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